Research on Big Data Processing and Visualization System in Computer-Assisted Macroeconomic Analysis

This study proposes a computer-assisted macroeconomic analysis system. The system combines big data processing and visualization technology, integrates machine learning and data mining algorithms, and aims to achieve accurate economic forecasting and analysis. The system first cleans, integrates and preprocesses massive economic data through the big data processing module, and uses advanced data mining technology to perform pattern recognition and trend analysis on historical economic data. By introducing machine learning algorithms to classify and regress economic data, accurate economic forecasts can be achieved. The system's visualization module intuitively presents economic trends, forecast results and influencing factors, helping decision makers to respond to macroeconomic changes in real time. The experimental results show that when predicting GDP growth rate, the system's error rate is 2.5 %, which is significantly lower than the 5.1 % of the traditional regression model. The results show that the system is superior to traditional methods in terms of prediction accuracy, especially when dealing with nonlinear economic problems. It shows stronger adaptability.